Lost in Words: Framing Effects on Public Willingness to Fight

Abstract Mobilizing citizens for defense is crucial in international conflicts, as demonstrated by recent events such as the Russia–Ukraine War in 2022. These conflicts highlight the critical importance of citizens’ willingness to fight. However, existing research, including that using the standard question in the World Values Survey (WVS), often overlooks a significant framing issue in measuring this willingness. This study addresses these gaps through theoretical and methodological perspectives. We argue that the way survey questions are framed can significantly influence responses. In particular, a value frame suggesting patriotism would increase willingness to fight, while a cost frame implying war-related costs would decrease it. Through conducting experimental surveys with varied wording on willingness to fight in Taiwan in 2024, we assess the impact of these different frames embedded in question wordings on responses to willingness to fight between two distinct groups: civilians and military recruits. We also measure the extent of social desirability bias that the value frame may induce. We have two major findings. First, the value frame would induce more willingness to fight while the cost frame dampens it. Second, military recruits display a lower willingness to fight compared to civilians, likely due to their greater awareness of the costs associated with war. This study emphasizes the need for carefully designed surveys and suggests alternative strategies of political communication to enhance the public willingness to fight among various groups, ensuring more accurate assessments of national defense preparedness.

Authors

Institutions

Publication Details

Journal
Public Opinion Quarterly
Published
2026-03-21
DOI
https://doi.org/10.1093/poq/nfag007
Primary Topic
Social and Intergroup Psychology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Lost in Words: Framing Effects on Public Willingness to Fight

Wen‐Chin Wu, Ding-Yi Lai, Chu-Ling Tseng, Wen-Cheng Fu
Public Opinion Quarterly
Social and Intergroup Psychology
article

Lost in Words: Framing Effects on Public Willingness to Fight

Wen‐Chin Wu, Ding-Yi Lai, Chu-Ling Tseng, Wen-Cheng Fu
article en

Abstract

Abstract Mobilizing citizens for defense is crucial in international conflicts, as demonstrated by recent events such as the Russia–Ukraine War in 2022. These conflicts highlight the critical importance of citizens’ willingness to fight. However, existing research, including that using the standard question in the World Values Survey (WVS), often overlooks a significant framing issue in measuring this willingness. This study addresses these gaps through theoretical and methodological perspectives. We argue that the way survey questions are framed can significantly influence responses. In particular, a value frame suggesting patriotism would increase willingness to fight, while a cost frame implying war-related costs would decrease it. Through conducting experimental surveys with varied wording on willingness to fight in Taiwan in 2024, we assess the impact of these different frames embedded in question wordings on responses to willingness to fight between two distinct groups: civilians and military recruits. We also measure the extent of social desirability bias that the value frame may induce. We have two major findings. First, the value frame would induce more willingness to fight while the cost frame dampens it. Second, military recruits display a lower willingness to fight compared to civilians, likely due to their greater awareness of the costs associated with war. This study emphasizes the need for carefully designed surveys and suggests alternative strategies of political communication to enhance the public willingness to fight among various groups, ensuring more accurate assessments of national defense preparedness.

Public Opinion Quarterly
National Defense University (US), National Defense University (TW), Institute of Mathematics, Academia Sinica (TW), Institute of Sociology, Academia Sinica (TW), Institute of Chemistry, Academia Sinica (TW), The University of Texas at Austin (US)
Openalex Percentile: Top 18%
Social and Intergroup Psychology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.